Field Optimization Tool for Maximizing Asset Value
- William J. Bailey (Schlumberger) | Benoit Couet (Schlumberger)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- February 2005
- Document Type
- Journal Paper
- 7 - 21
- 2005. Society of Petroleum Engineers
- 4.3.4 Scale, 2.3 Completion Monitoring Systems/Intelligent Wells, 5.1.5 Geologic Modeling, 1.6 Drilling Operations, 5.5.5 Evaluation of uncertainties, 3.3 Well & Reservoir Surveillance and Monitoring, 4.1.5 Processing Equipment, 5.5 Reservoir Simulation, 5.4.2 Gas Injection Methods, 5.5.8 History Matching, 5.6.3 Deterministic Methods, 4.1.2 Separation and Treating
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In this paper, we propose an optimization framework for maximizing assetvalue, both with and without uncertainty. We first present the methodology totreat a general control optimization in the presence of uncertainty, followedby a brief section on the optimization algorithms used. We then describe thefield model example used to illustrate the application of the methodology.Through a systematic analysis of various deterministic and stochastic cases, weaddress the various objectives sought. Using net present value (NPV) as ameasure, we also explore the valuation of advanced completions along with thereturns gained from expanding surface gas-handling facilities. The method alsogenerates an efficient frontier that can be used for risk and decisionanalysis. The results clearly demonstrate the value of such a framework forvalue maximization in planning both near- and long-term time horizons as wellas providing the necessary foundation for maximizing asset value.
We consider an existing infill program for a mature real onshore oil and gasfield with the objective of maximizing asset value. We do so by optimizing ahistory-matched reservoir model, and we provide confidence levels underuncertainty by generating efficient frontiers.
Application of search or optimization algorithms has been the subject ofnumerous studies and articles both inside and outside the petroleumindustry.1-14 Following from the work of Raghuraman et al.,1 this paperconsiders a real reservoir and attempts to maximize its value by analyzingvarious exploitation scenarios.
The paper first describes the main features of the framework: the overallmethodology and different optimization schemes. It then applies theoptimization process to the field example. While maximizing asset value withand without the presence of uncertainty, the efficient frontier is discussedand its use for risk management and decision making is demonstrated.
The process of optimizing a reservoir, under the assumption that everythingis deterministically known, is relatively straightforward. One may want toextract the maximum fraction of oil and/or minimize the water production ormaximize the NPV of the oil produced by optimally controlling variousoperational variables (e.g., individual-completion flow rates), all the whileaccounting for physical constraints (e.g., single-well production or pump/valvelimitations) and economic constraints (e.g., drilling, logging, or stimulationcosts). However, the presence of physical and/or financial uncertaintieselevates the problem of optimization to the level of a risk-management problem.A framework has been developed that encompasses the necessary elements toperform reservoir optimization under uncertainty and to provide the riskanalysis necessary for decision making. A detailed description of the process,with an example on reservoir monitoring and control, is given in Raghuraman etal.1 Fig. 1 shows a schematic of the algorithm for a problem withuncertainty.
|File Size||2 MB||Number of Pages||15|
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